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The Universal Remote Control for AI — Alex Hancock, Block

The Universal Remote Control for AI — Alex Hancock, Block

Alex Hancock discusses the need for a standardized protocol for client-to-agent communication in AI, similar to how MCP standardizes agent-to-tool interaction. He introduces the Agent Client Protocol (ACP), born from Zed and JetBrains, as a JSON RPC-based solution for client software to control agent harnesses, send tasks, and receive updates. Hancock demonstrates ACP's flexibility with multiple clients driving a single agent and highlights how its new remote transport capability, combined with MCP and model APIs, enables independent placement of all agentic stack components, fostering a competitive ecosystem that will significantly enhance user experience.

500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents — Ajay Prakash, LinkedIn

500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents — Ajay Prakash, LinkedIn

LinkedIn revolutionized its approach to AI agents by addressing the inherent limitations of LLMs in complex enterprise environments. Facing issues like hallucinations due to a lack of internal context, they developed a system of "playbooks" — structured, self-contained instructions published as tools. To scale beyond typical MCP limitations, they introduced three meta-tools (search, get schema, execute), enabling agents to dynamically discover and utilize thousands of internal tools and playbooks. This self-improving, context-aware infrastructure empowers agents to handle tasks from incident response to code generation, significantly boosting developer productivity and ensuring reliability.

MCPs for Observability Stacks

MCPs for Observability Stacks

Diana Todea, Head of Developer Relations at VictoriaMetrics, demonstrates how Model-Controller-Pair (MCP) servers enhance observability stacks for faster, smarter troubleshooting. She highlights the use of AI-driven anomaly detection, natural language querying, and customizable "skills" to investigate production issues, manage metrics, and generate alerts, showcasing practical applications with two interconnected MCP servers.

MCP Goes Stateless | ​John Dellenbaugh & Pankaj Kumar | MCP Release Party - Seattle

MCP Goes Stateless | ​John Dellenbaugh & Pankaj Kumar | MCP Release Party - Seattle

This session details the transformation of the MCP protocol to a stateless design, addressing previous scaling challenges by externalizing session state to a database and eliminating the need for sticky sessions and complex infrastructure. The presentation includes a live demo comparing stateful and stateless architectures, highlighting benefits in scalability and simplified deployment. It also covers considerations for security and data resiliency within this new paradigm.

Policy Enforcement and Tamper-Evident Audit Chains | ​Imran Siddique | MCP Release Party - Seattle

Policy Enforcement and Tamper-Evident Audit Chains | ​Imran Siddique | MCP Release Party - Seattle

Imran Siddique introduces cMCP, an open-source gateway that enhances Modular Control Plane (MCP) servers with policy enforcement and tamper-evident audit trails. It achieves this by running Cedar policy evaluation within Trusted Execution Environments (TEEs), ensuring that agent actions are governed securely and verifiably. The talk delves into the concept of "beyond governance" towards verifiable AI, the 'trace' standard for auditable logging, and the importance of confidential computing for regulated industries.

5 Ways to Connect AI Agents to Tools: From APIs to MCP

5 Ways to Connect AI Agents to Tools: From APIs to MCP

Grant Miller outlines five evolving patterns for integrating AI agents with tools, starting from simple direct API connections to complex, secure token-based architectures. The discussion highlights the progression of these methods, emphasizing how authentication, user delegation, abstraction layers like MCP, and secure credential management using vaults improve security, observability, and scalability in agentic systems.